For 2023, the health costs (combined medical and pharmacy benefit expenses) of U.S. employers for employees after plan and contribution changes are forecasted to increase by 6 percent. This survey represents US company's health care cost trends from 1999 to 2023.

Population Health (BRFSS: HRQOL)

Examining Trends, Disparities and Determinants of Health in the US Population

By Health [source]

About this dataset

The Behavioral Risk Factor Surveillance System (BRFSS) offers an expansive collection of data on the health-related quality of life (HRQOL) from 1993 to 2010. Over this time period, the Health-Related Quality of Life dataset consists of a comprehensive survey reflecting the health and well-being of non-institutionalized US adults aged 18 years or older. The data collected can help track and identify unmet population health needs, recognize trends, identify disparities in healthcare, determine determinants of public health, inform decision making and policy development, as well as evaluate programs within public healthcare services.

The HRQOL surveillance system has developed a compact set of HRQOL measures such as a summary measure indicating unhealthy days which have been validated for population health surveillance purposes and have been widely implemented in practice since 1993. Within this study's dataset you will be able to access information such as year recorded, location abbreviations & descriptions, category & topic overviews, questions asked in surveys and much more detailed information including types & units regarding data values retrieved from respondents along with their sample sizes & geographical locations involved!

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How to use the dataset

This dataset tracks the Health-Related Quality of Life (HRQOL) from 1993 to 2010 using data from the Behavioral Risk Factor Surveillance System (BRFSS). This dataset includes information on the year, location abbreviation, location description, type and unit of data value, sample size, category and topic of survey questions.

Using this dataset on BRFSS: HRQOL data between 1993-2010 will allow for a variety of analyses related to population health needs. The compact set of HRQOL measures can be used to identify trends in population health needs as well as determine disparities among various locations. Additionally, responses to survey questions can be used to inform decision making and program and policy development in public health initiatives.

Research Ideas

• Analyzing trends in HRQOL over the years by location to identify disparities in health outcomes between different populations and develop targeted policy interventions.
• Developing new models for predicting HRQOL indicators at a regional level, and using this information to inform medical practice and public health implementation efforts.
• Using the data to understand differences between states in terms of their HRQOL scores and establish best practices for healthcare provision based on that understanding, including areas such as access to care, preventative care services availability, etc

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

See the dataset description for more information.

Columns

File: rows.csv | Column name | Description | |:-------------------------------|:----------------------------------------------------------| | Year | Year of survey. (Integer) | | LocationAbbr | Abbreviation of location. (String) | | LocationDesc | Description of location. (String) | | Category | Category of survey. (String) | | Topic | Topic of survey. (String) | | Question | Question asked in survey. (String) | | DataSource | Source of data. (String) | | Data_Value_Unit | Unit of data value. (String) | | Data_Value_Type | Type of data value. (String) | | Data_Value_Footnote_Symbol | Footnote symbol for data value. (String) | | Data_Value_Std_Err | Standard error of the data value. (Float) | | Sample_Size | Sample size used in sample. (Integer) | | Break_Out | Break out categories used. (String) | | Break_Out_Category | Type break out assessed. (String) | | **GeoLocation*...

The HCUP Summary Trend Tables include monthly information on hospital utilization derived from the HCUP State Inpatient Databases (SID) and HCUP State Emergency Department Databases (SEDD). Information on emergency department (ED) utilization is dependent on availability of HCUP data; not all HCUP Partners participate in the SEDD. The HCUP Summary Trend Tables include downloadable Microsoft® Excel tables with information on the following topics: Overview of monthly trends in inpatient and emergency department utilization All inpatient encounter types Inpatient stays by priority conditions -COVID-19 -Influenza -Other acute or viral respiratory infection Inpatient encounter type -Normal newborns -Deliveries -Non-elective inpatient stays, admitted through the ED -Non-elective inpatient stays, not admitted through the ED -Elective inpatient stays Inpatient service line -Maternal and neonatal conditions -Mental health and substance use disorders -Injuries -Surgeries -Other medical conditions Emergency department treat-and-release visits Emergency department treat-and-release visits by priority conditions -COVID-19 -Influenza -Other acute or viral respiratory infection Description of the data source, methodology, and clinical criteria

Health, United States is an annual report on trends in health statistics. The report consists of two main sections: A chartbook containing text and figures that illustrates major trends in the health of Americans and a trend tables section that contains 156 detailed data tables. The two main components are supplemented by an executive summary, a highlights section, an extensive appendix and reference section, and an index.Note to Users: This CD is part of a collection located in the Da ta Archive of the Odum Institute for Research in Social Science at the University of North Carolina at Chapel Hill. The collection is located in Room 10, Manning Hall. Users may check the CDs out subscribing to the honor system. Items can be checked out for a period of two weeks. Loan forms are located adjacent to the collection.

Big Data in Healthcare Market Outlook

According to our latest research, the global Big Data in Healthcare market size reached USD 41.2 billion in 2024, demonstrating robust expansion driven by the increasing adoption of advanced analytics and data-driven decision-making in the healthcare sector. The market is projected to grow at a CAGR of 17.4% from 2025 to 2033, reaching an estimated value of USD 154.1 billion by 2033. This significant growth is primarily attributed to the surging volume of healthcare data, advancements in artificial intelligence and machine learning, and the increasing focus on improving patient outcomes and operational efficiency across healthcare institutions worldwide.

One of the primary growth factors fueling the Big Data in Healthcare market is the exponential rise in healthcare data generation, driven by the widespread adoption of electronic health records (EHRs), wearable devices, and connected medical equipment. As healthcare organizations seek to harness actionable insights from this data deluge, the demand for advanced analytics solutions has surged. The integration of big data analytics enables providers to enhance clinical decision-making, reduce medical errors, and optimize treatment protocols, thereby improving patient care and safety. Furthermore, the growing emphasis on value-based care models has compelled healthcare stakeholders to invest in robust data analytics platforms that can support population health management and evidence-based medicine, further accelerating market expansion.

Another key driver of the Big Data in Healthcare market is the growing need for cost containment and operational efficiency within healthcare organizations. Rising healthcare costs, resource constraints, and the increasing complexity of healthcare delivery have prompted providers and payers to leverage big data analytics to streamline operations, reduce redundancies, and enhance resource allocation. Financial analytics applications, in particular, are witnessing substantial uptake as organizations strive to identify cost-saving opportunities, detect fraudulent claims, and improve revenue cycle management. Additionally, operational analytics solutions are being deployed to optimize supply chain management, workforce planning, and facility utilization, resulting in enhanced productivity and reduced overheads.

The rapid advancement of artificial intelligence (AI), machine learning, and cloud computing technologies has also played a pivotal role in propelling the Big Data in Healthcare market forward. AI-driven analytics platforms are enabling healthcare providers to uncover hidden patterns in patient data, predict disease outbreaks, and personalize treatment plans based on individual patient profiles. The proliferation of cloud-based solutions has further democratized access to advanced analytics tools, allowing even small and medium-sized healthcare organizations to leverage big data capabilities without significant upfront investments in IT infrastructure. This technological evolution is expected to continue driving innovation and adoption across the global healthcare landscape.

From a regional perspective, North America continues to dominate the Big Data in Healthcare market, accounting for the largest revenue share in 2024, followed by Europe and Asia Pacific. The region's leadership is underpinned by robust healthcare IT infrastructure, high adoption rates of electronic health records, and strong government initiatives promoting data interoperability and healthcare digitization. Meanwhile, Asia Pacific is poised for the fastest growth during the forecast period, fueled by rapid healthcare modernization, expanding digital health initiatives, and increasing investments in healthcare analytics by both public and private sectors. As healthcare systems worldwide continue to prioritize data-driven transformation, the market's regional landscape is expected to evolve, with emerging economies playing an increasingly prominent role in shaping future growth trajectories.

The dataset contains estimates for the number of healthcare professionals in 15 different healthcare categories (e.g., Registered Nurse, Dentist, License Clinical Social Worker, etc.) based on completion of license renewal by Race/Ethnicity. There are two timeframes: all current licenses and recent licenses (since 2017). California population estimates are also included to provide a marker for each Race/Ethnicity. Each healthcare professional category can be compared across Race/Ethnicity groups and compared to statewide population estimates, so Race/Ethnicity shortages can be identified for each healthcare professional category. For instance, a notable difference between healthcare professional category and statewide population would indicate either underrepresentation or overrepresentation for that Race/Ethnicity, depending on the direction of the difference.

Health, United States is the report on the health status of the country. Every year, the report presents an overview of national health trends organized around four subject areas: health status and determinants, utilization of health resources, health care resources, and health care expenditures and payers.

Health All In One Machine Market Outlook

The global market size for Health All In One Machines in 2023 is estimated to be around USD 15 billion, with a forecasted size of approximately USD 28 billion by 2032, reflecting a Compound Annual Growth Rate (CAGR) of 7%. The growth of this market is primarily driven by the increasing awareness of health and fitness, technological advancements, and the rising incidence of lifestyle-related diseases.

The demand for integrated health solutions has surged in recent years, driven by an increasing awareness of the importance of maintaining a healthy lifestyle. This trend is underscored by the rising prevalence of chronic diseases such as diabetes, hypertension, and cardiovascular disorders, which are often linked to sedentary lifestyles and poor dietary habits. Consequently, consumers are increasingly seeking comprehensive health solutions that offer multiple functionalities in a single device, thus fueling the growth of the Health All In One Machine market.

Technological advancements have also played a pivotal role in the expansion of this market. Innovations in sensor technologies, artificial intelligence, and data analytics have enabled the development of sophisticated health machines that can monitor a wide array of health parameters in real-time. These advancements have not only enhanced the accuracy and reliability of these machines but also made them more user-friendly, thereby broadening their appeal to a wider consumer base.

Moreover, the growing adoption of telemedicine and remote monitoring solutions has further bolstered the demand for Health All In One Machines. These devices offer the convenience of monitoring vital health metrics from the comfort of one's home, thereby reducing the need for frequent hospital visits. This is particularly beneficial for the elderly population and individuals with chronic conditions who require continuous health monitoring. The COVID-19 pandemic has further accentuated the need for such devices, as people have become more cautious about visiting healthcare facilities.

Regionally, North America dominates the market, driven by high healthcare expenditure, advanced healthcare infrastructure, and a large base of health-conscious consumers. The Asia Pacific region, however, is expected to witness the highest growth rate during the forecast period, attributed to the increasing disposable income, rapid urbanization, and growing awareness about health and wellness. Government initiatives aimed at promoting digital health and the proliferation of smart devices are also contributing to the market growth in this region.

Product Type Analysis

The Health All In One Machine market can be segmented into Fitness Machines, Diagnostic Machines, and Therapeutic Machines. Fitness machines are primarily designed to help users maintain physical fitness through various exercises. These machines often incorporate multiple functionalities such as cardio, strength training, and flexibility exercises, making them highly versatile. The increasing trend of home gyms and the growing popularity of fitness tracking have significantly driven the demand for these fitness machines.

Diagnostic machines, on the other hand, are equipped with sensors and software to monitor various health parameters such as heart rate, blood pressure, glucose levels, and more. These machines are highly sought after for their ability to provide real-time health data, aiding in early diagnosis and management of potential health issues. The advancement in wearable technology and mobile health applications has further propelled the demand for diagnostic machines, making them an integral part of personal health management.

Therapeutic machines are designed to offer treatments and therapies for various health conditions. These machines include features such as massage, electrical stimulation, and heat therapy, providing relief from pain and aiding in recovery from injuries. The increasing incidence of musculoskeletal disorders and the growing awareness of non-invasive treatment options have significantly contributed to the growth of this segment. The integration of therapeutic functionalities into all-in-one health machines has made them appealing to both individuals and healthcare providers.

Overall, the product type segmentation highlights the diverse functionalities that Health All In One Machines offer, catering to different aspects of health management. The continuous innovation and integration of advanced technologies are expected to further enhance

This dataset contains global health indicators such as life expectancy, mortality rates, vaccination coverage, and disease prevalence across different countries. It covers data from 2000 to 2023, allowing for trend analysis in global health. Columns: Country, Year, Life Expectancy, Infant Mortality Rate, Vaccination Coverage (%), Disease Prevalence (%), GDP per Capita, Region.

Healthcare Big Data Analytics Market Outlook

The global healthcare big data analytics market size is projected to achieve a robust growth trajectory, with a valuation of approximately USD 32 billion in 2023. It is anticipated to soar to around USD 115 billion by 2032, reflecting an impressive compound annual growth rate (CAGR) of 15.4%. This remarkable growth can largely be attributed to the increasing demand for efficient data management systems in the healthcare sector, the rising need for data-driven decision-making, and the expanding adoption of analytics in diverse healthcare applications. The integration of artificial intelligence and machine learning in analytics, the emphasis on personalized medicine, and the growing importance of predictive analytics are further propelling the market forward.

One of the key growth drivers in the healthcare big data analytics market is the rising necessity for cost reduction and improved operational efficiency within the healthcare sector. Hospitals and clinics are increasingly recognizing the value of analytics in streamlining processes, reducing waste, and enhancing patient care. By leveraging big data analytics, healthcare providers can gain insights into patient care patterns, optimize resource allocation, and minimize unnecessary expenditures. This drive towards efficiency is further bolstered by government initiatives and policies aimed at improving healthcare delivery and reducing costs, creating a fertile ground for the adoption of advanced analytics solutions.

Another significant factor contributing to the market's expansion is the growing emphasis on personalized and precision medicine. As healthcare providers aim to offer more tailored treatment options, the analysis of vast datasets becomes crucial. Big data analytics facilitates the identification of patterns and trends in patient data, enabling healthcare providers to make informed decisions regarding personalized treatment plans. Moreover, the continuous advancements in genomics and biotechnology are generating immense volumes of data, necessitating robust analytics solutions to derive actionable insights. This trend towards personalized care is expected to drive substantial investments in big data analytics technologies in the coming years.

Additionally, the increasing prevalence of chronic diseases and the aging global population are driving the demand for effective population health management. Big data analytics plays a pivotal role in analyzing population health trends, identifying at-risk individuals, and devising preventive strategies. Governments and healthcare organizations are increasingly focusing on population health analytics to enhance public health outcomes and reduce the burden on healthcare infrastructure. This growing demand for comprehensive population health management solutions is expected to be a significant driving force for the healthcare big data analytics market over the forecast period.

Healthcare Analytics & Medical Analytics are becoming increasingly vital in the pursuit of personalized and precision medicine. By leveraging these analytics, healthcare providers can delve deeper into patient data to uncover insights that inform individualized treatment plans. This approach not only enhances patient outcomes but also optimizes the use of healthcare resources. As the demand for personalized care continues to rise, the role of healthcare analytics in tailoring treatments to individual patient needs is expected to grow exponentially. The integration of advanced analytics tools into healthcare systems is facilitating a shift towards more patient-centric care models, thereby driving the adoption of these technologies across the sector.

The regional outlook for the healthcare big data analytics market shows a diverse growth pattern across different geographies. North America currently holds a significant share of the market, driven by the presence of advanced healthcare infrastructure, a high level of digitalization, and a strong focus on research and development. Europe is also witnessing considerable growth, with countries like Germany and the United Kingdom leading the charge in the adoption of analytics solutions. Meanwhile, the Asia Pacific region is poised to experience the fastest growth, fueled by rapid technological advancements, increasing healthcare investments, and the need to address healthcare challenges in densely populated regions. Latin America and the Middle East & Africa are expected to show steady growth, driven by improving healthcare infrastruct

Zip Code, Life expectancy; Cancer deaths per 100,000 people; Heart disease deaths per 100,000 people; Alzheimer’s disease deaths per 100,000 people; Stroke deaths per 100,000 people; Chronic lower respiratory disease deaths per 100,000 people; Unintentional injury deaths per 100,000 people; Diabetes deaths per 100,000 people; Influenza and pneumonia deaths per 100,000 people; Hypertension deaths per 100,000 people. Percentages unless otherwise noted. Source information provided at: https://www.sccgov.org/sites/phd/hi/hd/Documents/City%20Profiles/Methodology/Neighborhood%20profile%20methodology_082914%20final%20for%20web.pdf

BY: Maternal Mortality Ratio: National Estimate: per 100,000 Live Births data was reported at 1.000 Ratio in 2014. This records an increase from the previous number of 0.000 Ratio for 2013. BY: Maternal Mortality Ratio: National Estimate: per 100,000 Live Births data is updated yearly, averaging 20.000 Ratio from Dec 1985 (Median) to 2014, with 26 observations. The data reached an all-time high of 30.000 Ratio in 1991 and a record low of 0.000 Ratio in 2013. BY: Maternal Mortality Ratio: National Estimate: per 100,000 Live Births data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Belarus – Table BY.World Bank.WDI: Social: Health Statistics. Maternal mortality ratio is the number of women who die from pregnancy-related causes while pregnant or within 42 days of pregnancy termination per 100,000 live births.;The country data compiled, adjusted and used in the estimation model by the Maternal Mortality Estimation Inter-Agency Group (MMEIG). The country data were compiled from the following sources: civil registration and vital statistics; specialized studies on maternal mortality; population based surveys and censuses; other available data sources including data from surveillance sites.;;

Big Data Analytics In Healthcare Market size is estimated at USD 37.22 Billion in 2024 and is projected to reach USD 74.82 Billion by 2032, growing at a CAGR of 9.12% from 2026 to 2032.

Big Data Analytics In Healthcare Market: Definition/ Overview

Big Data Analytics in Healthcare, often referred to as health analytics, is the process of collecting, analyzing, and interpreting large volumes of complex health-related data to derive meaningful insights that can enhance healthcare delivery and decision-making. This field encompasses various data types, including electronic health records (EHRs), genomic data, and real-time patient information, allowing healthcare providers to identify patterns, predict outcomes, and improve patient care.

BY: Newly Infected with HIV: Adults (Aged 15+) and Children (Aged 0-14) data was reported at 1,000.000 Number in 2022. This records a decrease from the previous number of 1,100.000 Number for 2021. BY: Newly Infected with HIV: Adults (Aged 15+) and Children (Aged 0-14) data is updated yearly, averaging 1,200.000 Number from Dec 1990 (Median) to 2022, with 33 observations. The data reached an all-time high of 2,100.000 Number in 2014 and a record low of 100.000 Number in 1993. BY: Newly Infected with HIV: Adults (Aged 15+) and Children (Aged 0-14) data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Belarus – Table BY.World Bank.WDI: Social: Health Statistics. Number of adults (ages 15+) and children (ages 0-14) newly infected with HIV.;UNAIDS estimates.;;This indicator is related to Sustainable Development Goal 3.3.1 [https://unstats.un.org/sdgs/metadata/].

Health Nutrition and Population Statistics database provides key health, nutrition and population statistics gathered from a variety of international and national sources. Themes include global surgery, health financing, HIV/AIDS, immunization, infectious diseases, medical resources and usage, noncommunicable diseases, nutrition, population dynamics, reproductive health, universal health coverage, and water and sanitation.

This CD-ROM contains a selection of trend data on the health and well-being of older Americans from the Data Warehouse on Trends in Health and Aging as of August 2003. The Data Warehouse was developed by the National Center for Health Statistics (NCHS), Centers for Disease Control and Prevention, with support from the National Institute on Aging. Topics on the CD-ROM include the following categories: national and state resident population, living arrangements, life expectancy, mortality, inju ries, risk factors and disease prevention, health status and chronic conditions, functional status and disability, health care utilization, health care expenditures, health care insurance, and socio- economic status. The Beyond20/20 Browser on the CD-ROM gives users the ability to view, manipulate and transfer data from the tables in the CD- ROM. Note to Users: This CD is part of a collection located in the Data Archive at the Odum Institute for Research in Social Science, University of North Carolina at Chapel Hill. The collection is located in Room 10, Manning Hall. Users may check out the CDs, subscribing to the honor system. Items may be checked out for a period of two weeks. Loan forms are located adjacent to the collection.

Natural Health Trends common stock dividends paid from 2010 to 2025. Common stock dividends paid can be defined as the cash outflow for dividends paid on a company's common stock

Social Determinants of Health Market Outlook

According to our latest research, the global Social Determinants of Health (SDOH) market size reached USD 7.2 billion in 2024, reflecting robust momentum driven by the integration of advanced analytics and digital health solutions across healthcare ecosystems. The market is anticipated to expand at a CAGR of 22.8% from 2025 to 2033, with the total market size expected to reach USD 59.6 billion by 2033. This accelerated growth is primarily fueled by the increasing recognition of the critical impact that social, economic, and environmental factors have on health outcomes, as well as the growing adoption of value-based care models globally. As per our latest research, the demand for holistic patient care and the need to address health disparities are the main catalysts propelling the SDOH market forward.

The surge in the Social Determinants of Health market is fundamentally driven by the global shift towards preventive healthcare and population health management. Healthcare organizations are increasingly recognizing that clinical care alone accounts for only a fraction of overall health outcomes, with social determinants such as housing, education, employment, and food security playing a pivotal role. This realization is prompting investments in SDOH data collection, analytics, and intervention programs that enable healthcare providers and payers to identify at-risk populations, design targeted interventions, and ultimately improve health equity. The proliferation of electronic health records (EHRs) and interoperable data platforms is further facilitating the integration of SDOH insights into clinical workflows, enhancing the ability to deliver personalized and effective care.

Another major growth driver for the SDOH market is the transition to value-based care and risk-based reimbursement models. Governments and private payers worldwide are incentivizing healthcare organizations to focus on outcomes rather than volume, which necessitates a comprehensive understanding of the social and environmental factors influencing patient health. As a result, there is a growing demand for advanced analytics, machine learning, and artificial intelligence solutions that can process and interpret large volumes of SDOH data. These technologies are enabling stakeholders to stratify risk, predict adverse health events, and allocate resources more efficiently, thereby reducing costs and improving quality of care. The increasing availability of real-time data from wearable devices, mobile applications, and community sources is also expanding the scope and effectiveness of SDOH initiatives.

Furthermore, regulatory mandates and policy initiatives are playing a crucial role in accelerating the adoption of SDOH solutions. In the United States, for instance, the Centers for Medicare & Medicaid Services (CMS) and other agencies have introduced guidelines and incentive programs that require healthcare organizations to screen for and address social determinants as part of routine care. Similar efforts are being observed in Europe and Asia Pacific, where governments are prioritizing health equity and social inclusion in their public health agendas. These policies are not only driving demand for SDOH data analytics and intervention platforms but are also fostering collaboration between healthcare providers, payers, community organizations, and technology vendors, thereby creating a vibrant and dynamic market landscape.

From a regional perspective, North America continues to dominate the SDOH market, accounting for the largest share in 2024, followed by Europe and Asia Pacific. The United States, in particular, is at the forefront due to its advanced healthcare infrastructure, strong regulatory support, and early adoption of health IT solutions. However, Asia Pacific is expected to witness the fastest growth over the forecast period, driven by rapid urbanization, rising healthcare expenditures, and increasing awareness of social health disparities. Europe also presents significant opportunities, especially with the implementation of digital health strategies and cross-sector collaborations aimed at addressing the root causes of health inequities. Latin America and the Middle East & Africa are gradually catching up, supported by government-led health reforms and international investments in healthcare infrastructure.

{"en": "The 2018 global health financing report presents health spending data for all WHO Member States between 2000 and 2016 based on the SHA 2011 methodology. It shows a transformation trajectory for the global spending on health, with increasing domestic public funding and declining external financing. This report a so presents, for the first time, spending on primary health care and specific diseases and looks closely at the relationship between spending and service coverage.\r The report\u2019s key messages include:\r Global trends in health spending confirm the transformation of the world\u2019s funding of health services.\r Domestic spending on health is central to universal health coverage, but there is no clear trend of increased government priority for health.\r Primary health care is a priority for expenditure tracking.\r Allocations across disease and interventions differ between external and government sources and\r Performance of government spending on health can improve.", "lo": "", "km": "", "th": "", "vi": "", "my": ""}